lr: 1e-05
sub_14:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.7879 - F1: 0.7746
sub_16:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.7188 - F1: 0.7163
sub_24:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.8750 - F1: 0.8750
sub_5:Test (Best Model) - Loss: 0.6025 - Accuracy: 0.9688 - F1: 0.9685
sub_19:Test (Best Model) - Loss: 0.7505 - Accuracy: 0.4688 - F1: 0.3637
sub_6:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.7500 - F1: 0.7500
sub_13:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.7500 - F1: 0.7490
sub_21:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.8788 - F1: 0.8759
sub_20:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.6037 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.6364 - F1: 0.6360
sub_3:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.6875 - F1: 0.6537
sub_22:Test (Best Model) - Loss: 0.5950 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.7188 - F1: 0.7046
sub_4:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.7273 - F1: 0.7179
sub_27:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.8788 - F1: 0.8759
sub_26:Test (Best Model) - Loss: 0.6411 - Accuracy: 0.7879 - F1: 0.7847
sub_23:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.9091 - F1: 0.9091
sub_1:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.9688 - F1: 0.9680
sub_28:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.8750 - F1: 0.8667
sub_16:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.4375 - F1: 0.4000
sub_8:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.4688 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 0.5932 - Accuracy: 0.9697 - F1: 0.9692
sub_29:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.8438 - F1: 0.8303
sub_14:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.9062 - F1: 0.9062
sub_11:Test (Best Model) - Loss: 0.6620 - Accuracy: 0.8788 - F1: 0.8778
sub_7:Test (Best Model) - Loss: 0.5601 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.6099 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.9062 - F1: 0.9062
sub_10:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.9062 - F1: 0.9015
sub_5:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.6562 - F1: 0.6390
sub_19:Test (Best Model) - Loss: 0.6268 - Accuracy: 0.8750 - F1: 0.8745
sub_15:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.7812 - F1: 0.7625
sub_25:Test (Best Model) - Loss: 0.6020 - Accuracy: 0.8788 - F1: 0.8787
sub_16:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.8750 - F1: 0.8745
sub_14:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.6562 - F1: 0.5594
sub_22:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.4688 - F1: 0.3637
sub_23:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.9091 - F1: 0.9077
sub_2:Test (Best Model) - Loss: 0.6419 - Accuracy: 0.9394 - F1: 0.9389
sub_9:Test (Best Model) - Loss: 0.6147 - Accuracy: 0.9688 - F1: 0.9685
sub_28:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.6875 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.8750 - F1: 0.8750
sub_12:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.9062 - F1: 0.9015
sub_11:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.4848 - F1: 0.4527
sub_17:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.6970 - F1: 0.6944
sub_27:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.6970 - F1: 0.6944
sub_3:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.8125 - F1: 0.7922
sub_4:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.9091 - F1: 0.9060
sub_21:Test (Best Model) - Loss: 0.6054 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.6216 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.6249 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.6180 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.6264 - Accuracy: 0.8438 - F1: 0.8436
sub_16:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.8750 - F1: 0.8730
sub_2:Test (Best Model) - Loss: 0.6041 - Accuracy: 0.8485 - F1: 0.8390
sub_22:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.5608
sub_6:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.6875 - F1: 0.6875
sub_24:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.6875 - F1: 0.6825
sub_7:Test (Best Model) - Loss: 0.6083 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.7879 - F1: 0.7806
sub_17:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.7879 - F1: 0.7806
sub_19:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6562 - F1: 0.6476
sub_8:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.9375 - F1: 0.9352
sub_20:Test (Best Model) - Loss: 0.6212 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.7576 - F1: 0.7519
sub_14:Test (Best Model) - Loss: 0.5938 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.5938 - F1: 0.5934
sub_1:Test (Best Model) - Loss: 0.5577 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.6042 - Accuracy: 0.9091 - F1: 0.9077
sub_26:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.8788 - F1: 0.8778
sub_16:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.2812 - F1: 0.2633
sub_25:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.6667 - F1: 0.6654
sub_5:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.9375 - F1: 0.9373
sub_3:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.7188 - F1: 0.7185
sub_28:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.9688 - F1: 0.9685
sub_23:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.9091 - F1: 0.9077
sub_9:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.8125 - F1: 0.8118
sub_29:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.6250 - F1: 0.6190
sub_2:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4242 - F1: 0.4046
sub_11:Test (Best Model) - Loss: 0.6446 - Accuracy: 0.8182 - F1: 0.8096
sub_10:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.5966 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.6090 - Accuracy: 0.8750 - F1: 0.8667
sub_12:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.8125 - F1: 0.8125
sub_18:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.9394 - F1: 0.9393
sub_8:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.8125 - F1: 0.8118
sub_4:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.9394 - F1: 0.9389
sub_14:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6562 - F1: 0.6532
sub_19:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.9375 - F1: 0.9373
sub_20:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.9062 - F1: 0.9015
sub_22:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.9688 - F1: 0.9680
sub_6:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.4375 - F1: 0.3455
sub_24:Test (Best Model) - Loss: 0.6004 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.6018 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.6257 - Accuracy: 0.9062 - F1: 0.9062
sub_26:Test (Best Model) - Loss: 0.5699 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.5694 - Accuracy: 0.9375 - F1: 0.9352
sub_2:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5152 - F1: 0.4923
sub_29:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.7500 - F1: 0.7490
sub_16:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5312 - F1: 0.5308
sub_25:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4545 - F1: 0.4107
sub_17:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.9697 - F1: 0.9692
sub_12:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.9062 - F1: 0.9015
sub_10:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.7812 - F1: 0.7810
sub_3:Test (Best Model) - Loss: 0.6042 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.6125 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.8750 - F1: 0.8667
sub_27:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.9697 - F1: 0.9692
sub_23:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6061 - F1: 0.5815
sub_15:Test (Best Model) - Loss: 0.5921 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.5913 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.5835 - Accuracy: 0.9394 - F1: 0.9380
sub_8:Test (Best Model) - Loss: 0.6211 - Accuracy: 0.8125 - F1: 0.7922
sub_5:Test (Best Model) - Loss: 0.5466 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.6129 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.6249 - Accuracy: 0.9091 - F1: 0.9091
sub_9:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.6250 - F1: 0.6235
sub_6:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.8750 - F1: 0.8704
sub_12:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.7812 - F1: 0.7519
sub_28:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.8438 - F1: 0.8359
sub_24:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.9375 - F1: 0.9373
sub_11:Test (Best Model) - Loss: 0.6060 - Accuracy: 0.9394 - F1: 0.9389
sub_10:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.7500 - F1: 0.7460
sub_2:Test (Best Model) - Loss: 0.6106 - Accuracy: 0.9375 - F1: 0.9365
sub_19:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.7500 - F1: 0.7091
sub_7:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.8750 - F1: 0.8745
sub_23:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.8182 - F1: 0.8096
sub_21:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.5938 - F1: 0.4340
sub_8:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.7500 - F1: 0.7490
sub_1:Test (Best Model) - Loss: 0.6276 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.5938 - F1: 0.4340
sub_5:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.7812 - F1: 0.7519
sub_4:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.9091 - F1: 0.9091
sub_18:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.8438 - F1: 0.8436
sub_6:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6667 - F1: 0.6654
sub_26:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5625 - F1: 0.5333
sub_9:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.8750 - F1: 0.8750
sub_25:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.8788 - F1: 0.8731
sub_16:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5000 - F1: 0.4459
sub_27:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.8485 - F1: 0.8390
sub_19:Test (Best Model) - Loss: 0.6249 - Accuracy: 0.6875 - F1: 0.6135
sub_28:Test (Best Model) - Loss: 0.5942 - Accuracy: 0.8438 - F1: 0.8303
sub_17:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.8485 - F1: 0.8390
sub_22:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.8788 - F1: 0.8787
sub_5:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5938 - F1: 0.5733
sub_12:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.7879 - F1: 0.7664
sub_20:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.8125 - F1: 0.8118
sub_24:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.8438 - F1: 0.8436
sub_10:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.5938 - F1: 0.5836
sub_14:Test (Best Model) - Loss: 0.5873 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.9688 - F1: 0.9685
sub_8:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.8438 - F1: 0.8359
sub_3:Test (Best Model) - Loss: 0.6189 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5625 - F1: 0.5152
sub_11:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.8182 - F1: 0.8167
sub_26:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.6199 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.7879 - F1: 0.7847
sub_15:Test (Best Model) - Loss: 0.5933 - Accuracy: 0.8750 - F1: 0.8745
sub_23:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5000 - F1: 0.4459
sub_21:Test (Best Model) - Loss: 0.6144 - Accuracy: 0.8125 - F1: 0.8125
sub_16:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.8125 - F1: 0.7922
sub_6:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.7879 - F1: 0.7806
sub_13:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.8788 - F1: 0.8731
sub_20:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.8438 - F1: 0.8303
sub_2:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.8125 - F1: 0.8095
sub_17:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.7576 - F1: 0.7556
sub_12:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.7576 - F1: 0.7519
sub_22:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.7576 - F1: 0.7519
sub_14:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.8125 - F1: 0.8125
sub_10:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.6150 - Accuracy: 0.9375 - F1: 0.9365
sub_8:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.8125 - F1: 0.8000
sub_27:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.7576 - F1: 0.7556
sub_25:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.8788 - F1: 0.8731
sub_28:Test (Best Model) - Loss: 0.6114 - Accuracy: 0.8750 - F1: 0.8667
sub_16:Test (Best Model) - Loss: 0.5859 - Accuracy: 0.9375 - F1: 0.9352
sub_5:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.9375 - F1: 0.9373
sub_19:Test (Best Model) - Loss: 0.6076 - Accuracy: 0.9375 - F1: 0.9352
sub_6:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.8788 - F1: 0.8778
sub_29:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.9375 - F1: 0.9373
sub_2:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.9688 - F1: 0.9685
sub_3:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.7879 - F1: 0.7879
sub_20:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.7812 - F1: 0.7703
sub_7:Test (Best Model) - Loss: 0.5512 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.8750 - F1: 0.8704
sub_12:Test (Best Model) - Loss: 0.6013 - Accuracy: 0.8485 - F1: 0.8390
sub_18:Test (Best Model) - Loss: 0.6172 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.8125 - F1: 0.8000
sub_1:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.7879 - F1: 0.7847
sub_4:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.9697 - F1: 0.9696
sub_22:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6061 - F1: 0.5926
sub_28:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.7812 - F1: 0.7703
sub_10:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.8438 - F1: 0.8359
sub_17:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.7576 - F1: 0.7519
sub_14:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.9688 - F1: 0.9680
sub_21:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.9688 - F1: 0.9685
sub_26:Test (Best Model) - Loss: 0.6041 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.7812 - F1: 0.7703
sub_11:Test (Best Model) - Loss: 0.5800 - Accuracy: 0.9697 - F1: 0.9696
sub_15:Test (Best Model) - Loss: 0.5562 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.9375 - F1: 0.9365
sub_18:Test (Best Model) - Loss: 0.6115 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.7576 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.6122 - Accuracy: 0.8485 - F1: 0.8390
sub_25:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.8750 - F1: 0.8745
sub_12:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.7273 - F1: 0.7179
sub_20:Test (Best Model) - Loss: 0.6249 - Accuracy: 0.8438 - F1: 0.8398
sub_28:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.7188 - F1: 0.7163
sub_1:Test (Best Model) - Loss: 0.6030 - Accuracy: 0.7879 - F1: 0.7664
sub_7:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.7500 - F1: 0.7229
sub_19:Test (Best Model) - Loss: 0.5747 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.7273 - F1: 0.7232
sub_3:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.8485 - F1: 0.8433
sub_2:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.9062 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 0.6230 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.8125 - F1: 0.7922
sub_4:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.9697 - F1: 0.9696
sub_8:Test (Best Model) - Loss: 0.6255 - Accuracy: 0.9062 - F1: 0.9054
sub_26:Test (Best Model) - Loss: 0.5969 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.9062 - F1: 0.9015
sub_24:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.5832 - Accuracy: 0.9394 - F1: 0.9380
sub_17:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.7576 - F1: 0.7556
sub_1:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.7273 - F1: 0.7179
sub_28:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.8788 - F1: 0.8731
sub_10:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.5995 - Accuracy: 0.9375 - F1: 0.9373
sub_19:Test (Best Model) - Loss: 0.6327 - Accuracy: 0.7500 - F1: 0.7091
sub_15:Test (Best Model) - Loss: 0.5642 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.9062 - F1: 0.9015
sub_5:Test (Best Model) - Loss: 0.5818 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.5811 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.8182 - F1: 0.8036
sub_21:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.8750 - F1: 0.8745
sub_4:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.8485 - F1: 0.8479
sub_27:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.7576 - F1: 0.7556
sub_1:Test (Best Model) - Loss: 0.6070 - Accuracy: 0.9394 - F1: 0.9389
sub_3:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.6364 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.8182 - F1: 0.8036
sub_11:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.7273 - F1: 0.7179
sub_14:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5938 - F1: 0.5934
sub_2:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.8485 - F1: 0.8433
sub_16:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.8438 - F1: 0.8303
sub_20:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.9394 - F1: 0.9380
sub_25:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.9375 - F1: 0.9365
sub_19:Test (Best Model) - Loss: 0.5766 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.6052 - Accuracy: 0.8750 - F1: 0.8704
sub_15:Test (Best Model) - Loss: 0.5972 - Accuracy: 0.9688 - F1: 0.9685
sub_9:Test (Best Model) - Loss: 0.6062 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.7812 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.6364 - F1: 0.5417
sub_23:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.7812 - F1: 0.7793
sub_24:Test (Best Model) - Loss: 0.6010 - Accuracy: 0.9375 - F1: 0.9373
sub_4:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.9697 - F1: 0.9696
sub_26:Test (Best Model) - Loss: 0.6087 - Accuracy: 0.9375 - F1: 0.9352
sub_10:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.7576 - F1: 0.7273
sub_17:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.9697 - F1: 0.9696
sub_2:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.8485 - F1: 0.8485
sub_29:Test (Best Model) - Loss: 0.5595 - Accuracy: 0.9688 - F1: 0.9685
sub_18:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.9375 - F1: 0.9373
sub_3:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5758 - F1: 0.5227
sub_20:Test (Best Model) - Loss: 0.6199 - Accuracy: 0.8485 - F1: 0.8433
sub_12:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.7500 - F1: 0.7409
sub_14:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.8750 - F1: 0.8667
sub_21:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.7188 - F1: 0.6946
sub_6:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.8788 - F1: 0.8778
sub_13:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.9697 - F1: 0.9696
sub_8:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.9688 - F1: 0.9680
sub_11:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.7576 - F1: 0.7556
sub_25:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.6875 - F1: 0.6875
sub_7:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.6060 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.4818
sub_2:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.8788 - F1: 0.8778
sub_10:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.8485 - F1: 0.8479
sub_1:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.9375 - F1: 0.9365
sub_26:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.8750 - F1: 0.8667
sub_24:Test (Best Model) - Loss: 0.6232 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.9688 - F1: 0.9685
sub_23:Test (Best Model) - Loss: 0.6004 - Accuracy: 0.8750 - F1: 0.8667
sub_14:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.9375 - F1: 0.9373
sub_5:Test (Best Model) - Loss: 0.6068 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6061 - F1: 0.5662
sub_17:Test (Best Model) - Loss: 0.6161 - Accuracy: 0.8788 - F1: 0.8787
sub_9:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.9375 - F1: 0.9373
sub_22:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.9062 - F1: 0.9054
sub_20:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.8438 - F1: 0.8398
sub_28:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.9091 - F1: 0.9088
sub_6:Test (Best Model) - Loss: 0.5928 - Accuracy: 0.9697 - F1: 0.9692
sub_7:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.6161 - Accuracy: 0.8788 - F1: 0.8787
sub_19:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.6875 - F1: 0.6863
sub_25:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.8788 - F1: 0.8787
sub_16:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.3750 - F1: 0.3074
sub_18:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.7500 - F1: 0.7091
sub_1:Test (Best Model) - Loss: 0.5711 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.6145 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5874 - Accuracy: 0.9688 - F1: 0.9680
sub_2:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6970 - F1: 0.6413
sub_13:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.9394 - F1: 0.9393
sub_11:Test (Best Model) - Loss: 0.6087 - Accuracy: 0.9091 - F1: 0.9091
sub_14:Test (Best Model) - Loss: 0.6394 - Accuracy: 0.8438 - F1: 0.8436
sub_22:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.6295 - Accuracy: 0.9062 - F1: 0.9054
sub_26:Test (Best Model) - Loss: 0.5806 - Accuracy: 0.9062 - F1: 0.9015
sub_4:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.9091 - F1: 0.9077
sub_21:Test (Best Model) - Loss: 0.5627 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5758 - F1: 0.5558
sub_12:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.8125 - F1: 0.8118
sub_28:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5312 - F1: 0.5308
sub_29:Test (Best Model) - Loss: 0.5998 - Accuracy: 0.8788 - F1: 0.8731
sub_16:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.7188 - F1: 0.6632
sub_9:Test (Best Model) - Loss: 0.6033 - Accuracy: 0.9375 - F1: 0.9352
sub_5:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.8750 - F1: 0.8667
sub_6:Test (Best Model) - Loss: 0.5442 - Accuracy: 0.9697 - F1: 0.9692
sub_17:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.7188 - F1: 0.6632
sub_23:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5455 - F1: 0.5171
sub_7:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.9375 - F1: 0.9373
sub_19:Test (Best Model) - Loss: 0.6517 - Accuracy: 0.7500 - F1: 0.7460
sub_24:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.7812 - F1: 0.7758
sub_15:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.8750 - F1: 0.8704
sub_27:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.7188 - F1: 0.6632
sub_3:Test (Best Model) - Loss: 0.6388 - Accuracy: 0.9697 - F1: 0.9692
sub_25:Test (Best Model) - Loss: 0.5727 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.6150 - Accuracy: 0.9062 - F1: 0.9015
sub_10:Test (Best Model) - Loss: 0.5850 - Accuracy: 0.9394 - F1: 0.9380
sub_2:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5152 - F1: 0.5038
sub_22:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.9688 - F1: 0.9680
sub_1:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.6414 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.7249 - Accuracy: 0.3750 - F1: 0.3074
sub_20:Test (Best Model) - Loss: 0.6334 - Accuracy: 0.8182 - F1: 0.8167
sub_8:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.6165 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6875 - F1: 0.6135
sub_11:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.7879 - F1: 0.7871
sub_26:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.9375 - F1: 0.9352
sub_4:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.8182 - F1: 0.8036
sub_17:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.8125 - F1: 0.8095
sub_28:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.6339 - Accuracy: 0.8750 - F1: 0.8704
sub_19:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.7188 - F1: 0.7117
sub_6:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.8182 - F1: 0.8139
sub_23:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.9091 - F1: 0.9060
sub_12:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.8125 - F1: 0.8118
sub_21:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.4375 - F1: 0.3455
sub_27:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.8125 - F1: 0.8095
sub_15:Test (Best Model) - Loss: 0.5724 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.7273 - F1: 0.7102
sub_9:Test (Best Model) - Loss: 0.6306 - Accuracy: 0.7812 - F1: 0.7519
sub_25:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.8438 - F1: 0.8424
sub_3:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.9091 - F1: 0.9077
sub_8:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.7812 - F1: 0.7703
sub_29:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 0.5987 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.7812 - F1: 0.7810
sub_11:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.8788 - F1: 0.8731
sub_24:Test (Best Model) - Loss: 0.6215 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.9688 - F1: 0.9680
sub_17:Test (Best Model) - Loss: 0.6219 - Accuracy: 0.8125 - F1: 0.7922
sub_4:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6667 - F1: 0.6330
sub_12:Test (Best Model) - Loss: 0.6294 - Accuracy: 0.8125 - F1: 0.8118
sub_13:Test (Best Model) - Loss: 0.6099 - Accuracy: 0.9375 - F1: 0.9365
sub_5:Test (Best Model) - Loss: 0.5858 - Accuracy: 0.9688 - F1: 0.9685
sub_28:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.8788 - F1: 0.8787
sub_9:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.5839 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.7273 - F1: 0.7232
sub_10:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.7879 - F1: 0.7847
sub_25:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.9688 - F1: 0.9685
sub_23:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.8788 - F1: 0.8778
sub_27:Test (Best Model) - Loss: 0.6219 - Accuracy: 0.8125 - F1: 0.7922
sub_18:Test (Best Model) - Loss: 0.5498 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.6250 - F1: 0.6113
sub_7:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.9062 - F1: 0.9015
sub_24:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.8125 - F1: 0.8057
sub_19:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.7812 - F1: 0.7519
sub_11:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.7273 - F1: 0.7263
sub_13:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.9062 - F1: 0.9015
sub_3:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.8485 - F1: 0.8479
sub_29:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6970 - F1: 0.6827
sub_1:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.8125 - F1: 0.8118
sub_4:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.9394 - F1: 0.9393
sub_17:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.3438 - F1: 0.3379
sub_11:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6061 - F1: 0.6046
sub_25:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.6076 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6250 - F1: 0.6113
sub_27:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.3438 - F1: 0.3379
sub_23:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.6970 - F1: 0.6944
sub_15:Test (Best Model) - Loss: 0.6419 - Accuracy: 0.9375 - F1: 0.9373
sub_13:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.8125 - F1: 0.7922
sub_7:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.8485 - F1: 0.8433
sub_17:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.9062 - F1: 0.9054
sub_11:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5152 - F1: 0.5111
sub_27:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.9062 - F1: 0.9054
sub_15:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.8438 - F1: 0.8424
sub_7:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.7500 - F1: 0.7490
sub_3:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.7879 - F1: 0.7746
sub_13:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.4062 - F1: 0.2889
sub_25:Test (Best Model) - Loss: 0.5719 - Accuracy: 0.9375 - F1: 0.9352
sub_23:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.8788 - F1: 0.8778
sub_21:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.7812 - F1: 0.7810
sub_7:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.9375 - F1: 0.9373
sub_25:Test (Best Model) - Loss: 0.6309 - Accuracy: 0.8438 - F1: 0.8436

=== Summary Results ===

acc: 82.04 ± 5.82
F1: 80.93 ± 6.38
acc-in: 86.66 ± 5.02
F1-in: 85.89 ± 5.41
